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Kursusbeskrivelse
Kursusnavn (dansk):Applied Statistics 
Kursusnavn (engelsk):Applied Statistics 
Semester:Forår 2019 
Udbydes under:Bachelor i datavidenskab (b-ds) 
Omfang i ECTS:7,50 
Kursussprog:Engelsk 
Kursushjemmeside:https://learnit.itu.dk 
Min. antal deltagere:
Forventet antal deltagere:
Maks. antal deltagere:90 
Formelle forudsætninger:The course is mandatory for first semester BSc in Data Science students.
The course is only open for students enrolled in BSc in Data Science or in BSc in Software Development. 
Læringsmål:After the course the student should be able to:

  • Apply fundamental definitions and theorems from probability theory and statistics

  • Perform basic computations on random variables and simulate random variables using R

  • Perform basic statistical modelling and inference (estimation and hypothesis testing) using mathematical analysis and in R

  • Analyse sampling distribution of estimators using both mathematical tools and simulation (bootstrapping) with R

  • Present a statistical analysis in a clear way that allows the reader to understand the conclusions and the assumptions they are based on

  • Do basic programming and data manipulation in R

  • Identify statistical problems in a given data analysis

 
Fagligt indhold:The course introduces the students to probability theory and applied statistics. It will focus on understanding the theoretical foundations of statistics and on applying the theory using mathematical analysis and simulations in R.

The subjects covered in the course include: probability spaces, random variables, conditional and joint probability, independence, expectation, variance, correlation and covariance, simulation of random variables, law of large numbers, central limit theorem, explorative data analysis, statistical models, bootstrapping, maximum likelihood estimation, confidence intervals, hypothesis testing. 
Læringsaktiviteter:14 ugers undervisning bestående af forelæsninger og øvelser

The lectures will introduce the theory and give examples of apply the theory. The weekly exercises will train the students on applying the theory and using R. The problems that the students solve in the weekly exercises will prepare the students for the written exam. 

Obligatoriske aktivititer:To qualify to the exam, the students have to have solved at least 50% of the problems prior to the weekly exercise session on average and, if randomly picked by the TA, present the solution to the class in the exercise session.

Be aware: The student will receive the grade NA (not approved) at the ordinary exam, if the mandatory activities are not approved and the student will use an exam attempt. 
Eksamensform og -beskrivelse:A22: Skriftlig eksamen (stedprøve) med restriktioner., (7-scale, internal exam)

4 hours written exam on premises with all written aids.

Restrictions: Access to the internet is not allowed, except access to LearnIT.
Students should bring a computer with the R programming language installed (with packages as specified by the teachers).  

 
Undervisere
Følgende personer underviser på kurset:
NavnStillingUndervisertypeIndsats (%)
Sami Brandt Lektor(ITU) Kursusansvarlig 50
Matteo Ceccarello Postdoc(ITU) Underviser 50
Frederik Enevoldsen Hjælpelærer(ITU) Hjælpelærer 0
Ksenia Klokova Hjælpelærer(ITU) Hjælpelærer 0
Luis Fernando Laris Pardo Hjælpelærer(ITU) Hjælpelærer 0